Embeddings in natural language processing, Pilehvar, Mohammad Taher Camacho-collados, Jose
Автор: Maosong Sun, Xiaojie Wang, Baobao Chang Название: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data ISBN: 3319690043 ISBN-13(EAN): 9783319690049 Издательство: Springer Рейтинг: Цена: 5300.00 р. Наличие на складе: Есть (3 шт.) Описание: This book constitutes the proceedings of the 16th China National Conference on Computational Linguistics, CCL 2017, and the 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017, held in Nanjing, China, in October 2017. Minority language information processing.
Автор: Joseph Olive, Caitlin Christianson, John McCary Название: Handbook of Natural Language Processing and Machine Translation ISBN: 1441977120 ISBN-13(EAN): 9781441977120 Издательство: Springer Рейтинг: Цена: 34937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program--The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation.The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research programs, each of the individual processes was performed separately and sequentially: speech recognition, language recognition, transcription, translation, and content summarization. The GALE program employed a distinctly new approach by executing these processes simultaneously. Speech and language recognition algorithms now aid translation and transcription processes and vice versa. This combination of previously distinct processes has produced significant research and performance breakthroughs and has fundamentally changed the natural language processing and machine translation fields.This comprehensive handbook provides an exhaustive exploration into these latest technologies in natural language, speech and signal processing, and machine translation, providing researchers, practitioners and students with an authoritative reference on the topic.
Автор: Pilehvar, Mohammad Taher Camacho-collados, Jose Название: Embeddings in natural language processing ISBN: 1636390218 ISBN-13(EAN): 9781636390215 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9286.00 р. Наличие на складе: Нет в наличии.
Описание: Provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings.
Автор: M?tais Название: Natural Language Processing and Information Systems ISBN: 3319417533 ISBN-13(EAN): 9783319417530 Издательство: Springer Рейтинг: Цена: 8944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, held in Salford, UK, in June 2016. The 17 full papers, 22 short papers, and 13 poster papers presented were carefully reviewed and selected from 83 submissions.
Автор: Abhijit Mishra, Pushpak Bhattacharyya Название: Cognitively Inspired Natural Language Processing ISBN: 9811315159 ISBN-13(EAN): 9789811315152 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book shows ways of augmenting the capabilities of Natural Language Processing (NLP) systems by means of cognitive-mode language processing.
Описание: If you`re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11504.00 р. Наличие на складе: Нет в наличии.
Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Автор: Dimitris N. Christodoulakis Название: Natural Language Processing - NLP 2000 ISBN: 3540676058 ISBN-13(EAN): 9783540676058 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume constitutes the refereed proceedings of the Second International Conference on Natural Language Processing, NLP 2000. Topics covered include: tokenization and morphological analysis; lexical knowledge representation; parsing and discourse analysis; and anaphora resolution.
Описание: Natural language understanding is central to the goals of artificial intelligence. Any truly intelligent machine must be capable of carrying on a conversation: dialogue, particularly clarification dialogue, is essential if we are to avoid disasters caused by the misunderstanding of the intelligent interactive systems of the future. This book is an interim report on the grand enterprise of devising a machine that can use natural language as fluently as a human. What has really been achieved since this goal was first formulated in Turing’s famous test? What obstacles still need to be overcome?
Описание: The Handbook provides a comprehensive overview of the concepts, methodologies, and applications being undertaken today in computational linguistics and natural language processing.
Автор: Ghosh Sohom, Gunning Dwight Название: Natural Language Processing Fundamentals ISBN: 1789954045 ISBN-13(EAN): 9781789954043 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Natural Language Processing Fundamentals starts with basics and goes on to explain various NLP tools and techniques that equip you with all that you need to solve common business problems for processing text.
Автор: Lotem Peled-Cohen, Roi Reichart, Rotem Dror, Segev Shlomov Название: Statistical Significance Testing for Natural Language Processing ISBN: 1681737957 ISBN-13(EAN): 9781681737959 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7207.00 р. Наличие на складе: Нет в наличии.
Описание: Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental.
The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.
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